Abstract P4-08-03: DEAD-box RNA helicase DP103 as a novel regulator of Wnt/β-catenin signaling pathway and promotes cancer stem cell-like behavior in triple negative breast cancers
Bibliographic record
Abstract
Abstract Despite recent advances in breast cancer therapeutics, mortality of metastatic triple negative breast cancer (TNBC) subtype remains high; due to their lack of hormone receptors expression for targeted therapy. Aberrant activation of Wnt/β-catenin signaling has been associated with breast cancers; where 40% of total breast cancers have elevated β-catenin levels with increased Wnt activity. Recently, we identified DEAD-box RNA helicase DP103 as a novel prognostic biomarker and metastasis-driving oncogene; highly expressed in TNBC subtype. Interestingly, we found high DP103 expression to be positively correlated with high β-catenin expression in clinical specimens (n=400). This led us to hypothesize a possible role of DP103 in modulating the Wnt/β-catenin pathway in TNBCs. Depletion of DP103 in metastatic TNBC cells decreases Wnt/β-catenin activity and expression of downstream Wnt target genes, while overexpression of DP103 increases Wnt activity. Depletion of DP103 also decreases phosphorylation of LRP6 and several important Wnt modulators required for downstream Wnt activation. Moreover, induction of Wnt/β-catenin signaling in Wnt responsive TNBC cells also significantly increased DP103 expression, indicating a possible positive feedback loop. Both canonical and non-canonical Wnt signaling is known to independently promote stem cell growth in mammospheres. Herein, we will also provide evidence on the role of DP103 in promoting breast cancer stem cell-like properties. Collectively, our data show a novel regulatory role of DP103 in the Wnt/β-catenin signaling pathway and in promoting breast cancer stem cell-like behavior, presenting itself as a potential drug target in TNBC patients. Citation Format: Cai W, Cheong JK, Edison E, Banerjee A, Tan TZ, Gaboury L, Yousef EM, Thiery JP, Lobie PE, Virshup DM, Yap CT, Kumar AP. DEAD-box RNA helicase DP103 as a novel regulator of Wnt/β-catenin signaling pathway and promotes cancer stem cell-like behavior in triple negative breast cancers. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P4-08-03.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".